collective/coldcallbot
17
0
Fork 0
Code

change assessment code for BSOC 2024

Browse Source
This commit is contained in:
Benjamin Mako Hill 2025-10-07 15:37:08 -07:00
parent f7270293f2
commit f6e4504491
1 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
assessment_and_tracking/compute_final_case_grades.R
View File

@ -1,6 +1,6 @@
## load in the data ## load in the data
################################# #################################
myuw <- read.csv("../data/2022_winter_COM_481_A_students.csv", stringsAsFactors=FALSE) myuw <- read.csv("../data/2024_autumn_COMMLD_570_A_joint_students.csv", stringsAsFactors=FALSE)
current.dir <- getwd() current.dir <- getwd()
source("../assessment_and_tracking/track_participation.R") source("../assessment_and_tracking/track_participation.R")
@ -11,20 +11,20 @@ call.list$timestamp <- as.Date(call.list$timestamp)
## class-level variables ## class-level variables
gpa.point.value <- 50/(4 - 0.7) gpa.point.value <- 50/(4 - 0.7)
question.grades <- c("PLUS"=100, "CHECK"=100-gpa.point.value, "MINUS"=100-(gpa.point.value*2)) ## question.grades <- c("GOOD"=100, "FAIR"=100-gpa.point.value, "BAD"=100-(gpa.point.value*2))
question.grades <- c("GOOD"=100, "SATISFACTORY"=100-gpa.point.value, "POOR"=100-(gpa.point.value*2), "NO MEANINGFUL ANSWER"=0)
missed.question.penalty <- gpa.point.value * 0.2 ## 1/5 of a full point on the GPA scale missed.question.penalty <- gpa.point.value * 0.2 ## 1/5 of a full point on the GPA scale
## inspect set the absence threashold ## inspect set the absence threashold
ggplot(d) + aes(x=absences) + geom_histogram(binwidth=1, fill="white",color="black") ggplot(d) + aes(x=absences) + geom_histogram(binwidth=1, fill="white",color="black")
absence.threshold <- median(d$absences) absence.threshold <- median(d$absences)
## inspect and set the questions cutoff ## inspect and set the questions cutoff
## questions.cutoff <- median(d$num.calls) ## questions.cutoff <- median(d$num.calls)
## median(d$num.calls) ## median(d$num.calls)
## questions.cutoff <- nrow(call.list) / nrow(d) ## TODO talk about this ## questions.cutoff <- nrow(call.list) / nrow(d) ## TODO talk about this
## this is the 95% percentile based on simulation in simulation.R ## this is the 95% percentile based on simulation in simulation.R
questions.cutoff <- 4 questions.cutoff <- 15
## show the distribution of assessments ## show the distribution of assessments
table(call.list$assessment) table(call.list$assessment)
@ -78,6 +78,7 @@ median(d$num.calls)
## helper function to generate average grade minus number of missing ## helper function to generate average grade minus number of missing
gen.part.grade <- function (x.unique.name) { gen.part.grade <- function (x.unique.name) {
q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]] q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]]
print(q.scores)
base.score <- mean(q.scores, na.rm=TRUE) base.score <- mean(q.scores, na.rm=TRUE)
## number of missing days ## number of missing days
@ -89,7 +90,6 @@ gen.part.grade <- function (x.unique.name) {
missing.in.class.days=missing.in.class.days) missing.in.class.days=missing.in.class.days)
} }
## create the base grades which do NOT include missing questions ## create the base grades which do NOT include missing questions
tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade)) tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade))
d <- merge(d, tmp) d <- merge(d, tmp)